Many small differences among individuals, rather than a single significant difference or a small number of large variations, may account for the differing effects of medications, new research suggests.

Drugs are not equally effective for everyone, due, at least in part, to the fact that our bodies take up pharmaceutical substances to varying degrees. Despite the fact that drugs don’t affect us all in the same way, however, little research has taken place to determine why.

Now, Ruedi Aebersold, a professor of systems biology at ETH Zurich, and colleagues shed some light on the subject in the journal Cell Systems.

The researchers performed detailed measurements of proteins and metabolites in cell culture experiments and showed that differing drug effects between individuals cannot be attributed to a single factor or even a few factors. Instead, the researchers found that many small differences together are responsible for the large variation.

In order to investigate the variable effects of drugs, the scientists analyzed cholesterol regulation in four different human cell lines. They tested how the cells responded differently to various drugs that affect cholesterol levels. The researchers measured and compared the concentrations of a large number of different proteins and metabolites in the cells at specific times. It turned out that each of the cell lines responded differently to the drugs.

“Contrary to what one might expect, the differences were not due to one cell line simply taking up more of a pharmaceutical substance than another, or that one cell lacked a central regulation mechanism found in another cell,” says Peter Blattmann, a postdoc in Aebersold’s group and first author of the study. Instead, the scientists showed that many enzymes and many of the complex biochemical pathways of a cell together contribute to the differences.

“Our findings clearly show that simply measuring the amount of drug uptake is not sufficient to understand inter-individual differences in effectiveness, an approach that was typically taken in the past,” says Blattmann. “Rather we have to adopt a holistic perspective, and, as we did in this study, use computer models to look also at other complex intracellular processes to understand why the drug response varies.”

The individual differences are even more pronounced in cancer treatments than in cholesterol-lowering medications. Especially in the case of more advanced medications, there are treatments that only work for a very small group of patients.

“The systems biology approach we took in our study might thus also make it possible to predict which patients respond well to a cancer drug and which will not,” says Blattmann.